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Investigation of low-density parity check codes concatenated multi-user massive multiple-input multiple-output systems with imperfect channel state information

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JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS 2022年第3期19卷 539-550页

作者： Bhardwaj, Lokesh Mishra, Ritesh Kumar Shankar, Ravi NIT Patna Dept Elect & Commun Engn Patna 800005 Bihar India Madanapalle Inst Technol & Sci Dept Elect & Commun Engn Madanapalle India Manav Rachna Univ Dept Elect & Commun Engn Faridabad India

In this era of communication technology, it is desirable to increase the data rate while minimizing the error to improve the system's reliability. One of these techniques is massive multiple-input multiple-output (mMIMO), which increases the spectral efficiency by providing the data to multiple users simultaneously through spatial multiplexing. The mMIMO system processes the received signal by prior estimation of the channel, which has a finite variance leading to imperfect channel state information (ICSI) at the receiver. In the fifth-generation technology, spectral efficiency using mMIMO may decrease as the number of subscribers increases, resulting in more interference and affecting system capacity. The ICSI provides another challenge, as the processed data at the receiver's output may now be more erroneous. Thus, this article provides an insight into the impact of an increase in the number of users on the variation in bit error rate with the signal-to-noise ratio in multi-user mMIMO (MU-mMIMO) and low-density parity check (LDPC) codes concatenated MU-mMIMO systems having ICSI at the receiver for quadrature amplitude modulation (QAM) and 16-QAM as modulation techniques. It has been shown that the performance of the concatenated scheme outperforms the conventional mMIMO system.

关键词： Channel estimation massive multiple-input multiple-output low-density parity check codes imperfect channel state information

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Secure downlink transmission with finite resolution analog beamforming in massive multiple-input multiple output system

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2018年第9期14卷 1-13页

作者： Zhang, Xianyu Guo, Daoxing Yang, Kongzhe Xie, Silin Army Engn Univ PLA Nanjing 210007 Jiangsu Peoples R China

To reduce the number of radio-frequency chains of base station, the use of finite resolution analog beamforming is desirbale in massive multiple-input multiple-output system. This article investigates the secure downlink massive multipleinput multiple-output data transmission with artificial noise at base station in the presence of a multi-antenna passive eavesdropper. The achievable user's ergodic information rate and ergodic capacity of the eavesdropper are analyzed in detail, respectively. With maximum ratio transmission or maximum ratio combining, we derive closed-form expressions for a tight lower bound on ergodic secrecy rate and tight upper bound for secrecy outage probability. Based on these analytical expressions, the effects of various system parameters on secrecy performance, such as power allocation factor, number of eavesdropper's antennas, number of the user terminals, total transmission power, and finite resolution analog beamforming parameters, are investigated in detail. Also, the optimal power allocation scheme between data and artificial noise signals is achieved in closed form to maximize the ergodic secrecy rate. In addition, we derive the conditions that the secure massive multiple-input multiple-output system need to meet to obtain a positive secrecy rate. Finally, numerical simulation results validate the system's secrecy performance and verify all the theoretical analytical results.

关键词： massive multiple-input multiple-output physical layer security finite resolution analog beamforming artificial noise ergodic secrecy rate

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Secure performance analysis and detection of pilot attack in massive multiple-input multiple-output system

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2018年第5期14卷

作者： Zhang, Xianyu Guo, Daoxing Guo, Kefeng Niu, Hehao Army Engn Univ PLA Haifuxiang 1 Nanjing 210007 Jiangsu Peoples R China

This article studies the physical layer security of massive multiple-input multiple-output system in time-division-duplex mode. Specifically, a single-cell downlink massive multiple-input multiple-output communication system is considered. The resulting achievable secrecy rate is investigated in the presence of passive or active eavesdroppers. The analytical results reveal that the massive multiple-input multiple-output system is naturally immune to passive eavesdroppers, but will be dramatically degraded by active attack. On account of the risk caused by active attack, a simple and effective detection algorithm is proposed. Uplink pilots with random phases are transmitted during the detection operation. By comparing the phase deviation change of the received pilot signals' cross product, the active eavesdroppers can be detected exactly. The closed-form expressions for probabilities of detection, false alarm, and false rejection are obtained respectively, which can demonstrate the robust performance of the proposed detection scheme. To maximize the secrecy energy efficiency of the system, the optimal power allocation strategy is studied under total power constraints. This optimization problem is efficiently solved by fractional programming. Numerical simulation results are derived to validate the secrecy performance of the massive multiple-input multiple-output system, the active pilot attacker detection performance, and the energy efficiency optimization effect.

关键词： massive multiple-input multiple-output physical layer security active pilot attack detection of active eavesdropping energy efficiency

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An energy efficient resource allocation and transmit antenna selection scheme in mm-wave using massive multiple-input multiple-output technology

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2022年第6期35卷 e5080-e5080页

作者： Singh, Charanjeet Kishoreraja, Parasuram Chandrasekaran SRM Univ Delhi NCR Dept Elect & Commun Engn Sonipat India

The massive multiple-input multiple-output (MIMO) improves the reliability of transmission and capacity of the channel. Resource allocation (RA) and transmit antenna selection (TAS) can minimize the complexity in implementation and hardware costs. In this research, both the RA and the TAS of wireless communication in millimeter-wave (mm-wave) with massive MIMO technology are considered. Two different solutions are developed for this research such as the deep learning method for efficient resource allocation process and optimization algorithm for TAS process. Here, the RA process is done with the help of attention-based capsule auto-encoder (ACAE) architecture which allocates the radio resources like power, space, time and frequency to all the available users in the system. Further, battle royale optimization (BRO) algorithm is utilized to select an efficient antenna from multiple antennas at BS. This optimization algorithm optimally selects an efficient antenna so that, user equipment (UEs) can create high quality links and achieves a reduced power consumption rate of the whole architecture. The overall system performance depends on the selection of optimal antenna which in terms enhances spectral efficiency (SE), energy efficiency (EE), reliability, and diversity gain of MIMO technology. In this way, both RA and optimal antenna selection schemes are performed to maximize the overall performance of wireless communication with massive MIMO technology for 5G wireless communication applications. The implementation of the proposed methodology is evaluated on MATLAB. Finally, the efficiency of the developed method is improved with respect to the capacity, EE, and SE.

关键词： deep learning method massive multiple-input multiple-output resource allocation transmit antenna selection process user equipment

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Channel capacity analysis of non-orthogonal multiple access and massive multiple-input multiple-output wireless communication networks considering perfect and imperfect channel state information

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JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS 2022年第4期19卷 771-781页

作者： Shankar, Ravi Nandi, Shovon Rupani, Ajay Madanapalle Inst Technol & Sci Wz 6 ViharPhase 1 Madanapalle 517325 India Bengal Inst Technol Dept Elect & Commun Engn Kolkata India Jodhpur Inst Engn & Technol Dept Elect & Commun Engn Jodhpur Rajasthan India

In this paper, we investigate the non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (M-MIMO) techniques and through simulation, and a comparison is given between the NOMA and orthogonal multiple access techniques. Integrating NOMA with M-MIMO is a very challenging task. In this paper, for a single-cell system, NOMA is integrated with a M-MIMO system for better spectral and energy efficiency. Investigation of the multiple user gain is the focus of this work because the multiple user gain supports simultaneous transmission of multiple users in the case of the M-MIMO system. In this way, the M-MIMO will provide a 100 times channel capacity increase, which results in very high data transmission rate. In the modern communication system, achieving multiple user gain is a very difficult task when channel estimation error is present. The performance of the orthogonal multiple access as well as NOMA system significantly reduced in the presence of channel estimation error. However, most of the current schemes do not work well with imperfect perfect channel state information conditions. Simulation results closely agree with the theoretical outcomes.

关键词： massive multiple-input multiple-output non-orthogonal multiple access channel estimation error wireless communication orthogonal multiple access

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Multi-Agent Federated Q-Learning Algorithms for Wireless Edge Caching

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第2期74卷 2973-2988页

作者： Liu, Zhikai Garg, Navneet Ratnarajah, Tharmalingam Univ Edinburgh Inst Imaging Data & Commun Sch Engn Edinburgh EH8 9YL Scotland Univ Edinburgh Inst Data Image & Commun Sch Engn Edinburgh EH8 9YL Scotland LNM Inst Informat Technol Dept Elect & Commun Engn Jaipur 302004 India

Edge caching is an increasingly vital technique in wireless networks, particularly needed to address users' repeated demands, including real-time traffic data and map access in vehicular communications. This paper presents a three-tier system for edge caching, integrating massive multiple-input multiple-output (mMIMO) networks. We consider a scenario with an extensive file library whose size is larger than the aggregated caching capacity of the small base stations (SBSs). Each SBS proactively caches files based on dynamic file popularity that is unknown in advance. A distinguishing aspect of our model is its file-wise approach to the cache instead of the conventional vector-wise methods based on aggregate popularity. This approach introduces additional computational challenges concerning the extensive file library. We formulated the optimization problem to maximize the long-term discounted cache hit rate while minimizing the delivery delay. For the solution, two multi-agent federated Q-learning algorithms are proposed. The first algorithm employs selective updates of the Q-values of popular files to minimize computational overhead. The second algorithm incorporates linear function approximation (LFA) and tensor completion (TC) to streamline the updating process further, reducing the required parameter number. Through the real-world MovieLens dataset and compared with various baseline algorithms, simulations demonstrate that our proposed algorithm can reduce the delay by around 2.60--21.29%, improve the cache hit rate by around 5.71--66.42%, and reduce the computational complexity by at most 97.91%.

关键词： Libraries Tensors Heuristic algorithms Delays Vehicle dynamics Computational modeling Vectors Real-time systems Matrix decomposition Communication system security Large file library linear function approximation massive multiple-input multiple-output tensor completion wireless edge caching

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Quantized Constant-Envelope Waveform Design for massive MIMO DFRC Systems

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第4期43卷 1056-1073页

作者： Wu, Zheyu Liu, Ya-Feng Chen, Wei-Kun Masouros, Christos Chinese Acad Sci Inst Computat Math & Sci Engn Comp Acad Math & Syst Sci State Key Lab Sci Engn Comp Beijing 100190 Peoples R China Beijing Inst Technol Sch Math & Stat Beijing Key Lab MCAACI Beijing 100081 Peoples R China UCL Dept Elect & Elect Engn London WC1E 7JE England

Both dual-functional radar-communication (DFRC) and massive multiple-input multiple-output (MIMO) have been recognized as enabling technologies for 6G wireless networks. This paper considers the advanced waveform design for hardware-efficient massive MIMO DFRC systems. Specifically, the transmit waveform is imposed with the quantized constant-envelope (QCE) constraint, which facilitates the employment of low-resolution digital-to-analog converters (DACs) and power-efficient amplifiers. The waveform design problem is formulated as the minimization of the mean square error (MSE) between the designed and desired beampatterns subject to the constructive interference (CI)-based communication quality of service (QoS) constraints and the QCE constraint. To solve the formulated problem, we first utilize the penalty technique to transform the discrete problem into an equivalent continuous penalty model. Then, we propose an inexact augmented Lagrangian method (ALM) algorithm for solving the penalty model. In particular, the ALM subproblem at each iteration is solved by a custom-built block successive upper-bound minimization (BSUM) algorithm, which admits closed-form updates, making the proposed inexact ALM algorithm computationally efficient. Simulation results demonstrate the superiority of the proposed approach over existing state-of-the-art ones. In addition, extensive simulations are conducted to examine the impact of various system parameters on the trade-off between communication and radar performances.

关键词： Measurement Symbols massive MIMO Quality of service Wireless networks Vectors Transmitting antennas Radar antennas Precoding Minimization Augmented Lagrangian method constructive interference dual-functional radar communication massive multiple-input multiple-output quantized constant envelope

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THzCondenser: A System Design for IRS-Aided Terahertz Wideband Communications

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2025年第3期24卷 2545-2558页

作者： Jiang, Yihang Gong, Yi Zhou, Ziqin Li, Xiaoyang Zhang, Rui Chinese Univ Hong Kong Shenzhen Res Inst Big Data Shenzhen 518172 Peoples R China Southern Univ Sci & Technol Dept Elect & Elect Engn Shenzhen 518055 Peoples R China Chinese Univ Hong Kong Shenzhen Res Inst Big Data Sch Sci & Engn Shenzhen 518172 Guangdong Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 119077 Singapore

With the access to tens of gigahertz of bandwidth, terahertz (THz) wideband communication emerges as a promising technology for the upcoming next generation mobile networks. To deal with the severe path loss and blockage of THz signals, massive multiple-input multiple-output and intelligent reflecting surface (IRS) can be jointly employed. Due to the extremely large signal bandwidth, the beams generated by the transmit hybrid beamforming may point to different directions around the target direction at different frequencies, which results in the beam splitting effect (BSE). In this paper, a new system design namely THzCondenser is introduced to mitigate the BSE, where the signals generated by each transmit radio frequency (RF) chain are reflected by one of the distributed IRSs in a one-to-one manner via the joint transmit and IRS beamforming design, thus creating adjustable multi-path components to achieve both high spatial multiplexing gain and array gain. Moreover, for practical scenarios when the number of transmit RF chains is more than that of IRSs, each IRS may need to reflect the signals generated by multiple RF chains in a one-to-many manner. For the above two cases, the joint beamforming design problems are efficiently solved to maximize the achievable rate. Simulations are conducted to verify the effectiveness of the proposed algorithms for mitigating the BSE and improving the achievable rate in IRS-aided THz wideband communications.

关键词： Terahertz communications Array signal processing Radio frequency Wideband Vectors OFDM Millimeter wave communication System analysis and design Space division multiplexing massive MIMO Terahertz wideband communication intelligent reflecting surface massive multiple-input multiple-output beam splitting hybrid beamforming

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Implementation of Hybrid Wild Geese Migration-Bird Swarm Algorithm-Based Optimal Power Allocation Strategy for Spectral Efficiency Analysis in massive MIMO System

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TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES 2025年第5期36卷

作者： Jallu, Swathi Raju, K. Padma Aditya Inst Technol & Management Dept ECE Tekkali India Jawaharlal Nehru Technol Univ Dept ECE Kakinada India

Spectral Efficiency (SE) plays a crucial role in designing and transmitting the amount of data in wireless communication systems that is an important measure for validating the effectiveness of cellular systems. It determines the usage of a limited frequency spectrum, but it fails to measure consumed power. Numerous methods have been developed to analyze the multiple-input multiple-output (MIMO) system with diverse channel methods. This MIMO system effectively enhances the data throughput, and it can serve diverse users simultaneously within the same frequency band. It significantly enhances the system framework and minimizes the impact of signal fading. However, the MIMO system faces challenges like lower transmit power, maximized coverage space, higher spectral efficiency, and multiplexing gain. To solve these issues, a novel optimization algorithm is developed in massive Multi-User MIMO (MU-MIMO) for maximizing SE in a Downlink (DL) system. This DL communication system is utilized to determine the complex channel conditions among the Base Station (BS) and user equipment. Also, it provides better data transmission control, and it carefully manages the signal strength in the MIMO system. Here, many antennas are provided in BS to distribute individual antenna consumers at the same time in a similar frequency band, and the duplex mode time division uses the beamforming training scheme. An optimal resource allocation together determines the DL transmission signal power training, Uplink (UL) transmission signal power training, UL transmission training duration, and DL transmission to increase the SE, data signal power initiated from the complete given energy budget. Since SE is the main concern of this work, this paper implements an efficient heuristic mechanism for increasing SE in a massive MIMO (M-MIMO) method. The M-MIMO system accurately provides the best cell edge coverage and maximizes network capacity. It achieves better spectral efficiency to enhance overall t

关键词： integrating the position of wild geese and bird swarm algorithm massive multiple-input multiple-output power and resource allocation spectral efficiency uplink and downlink transmission

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A survey on user-centric cell-free massive MIMO systems

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Digital Communications and Networks 2022年第5期8卷 695-719页

作者： Shuaifei Chen Jiayi Zhang Jing Zhang Emil Björnson Bo Ai School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong UniversityBeijing100044China Department of Computer Science KTH Royal Institute of TechnologySE-16440KistaSweden Department of Electrical Engineering(ISY) Linköping UniversitySE-58183LinköpingSweden State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing100044China

The mobile data traffic has been exponentially growing during the last several *** was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UDN))and/or the increased number of active antennas per Access Point(AP)(i.e.,massive multiple-input multiple-output(mMIMO)).However,neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation(6G)wireless communications due to the inter-cell interference and large quality-of-service ***-Free(CF)mMIMO,which combines the best aspects of UDN and mMIMO,is viewed as a key solution to this *** such systems,each User Equipment(UE)is served by a preferred set of surrounding APs *** this paper,we provide a survey of the state-of-the-art literature on CF *** a starting point,the significance and the basic properties of CF mMIMO are *** then present the canonical framework to discuss the essential details(i.e.,transmission procedure and mathematical system model).Next,we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and *** that,we discuss the practical issues in implementing CF mMIMO and point out the potential future ***,we conclude this paper with a summary of the key lessons learned in this field.

关键词： 6G network User-centric cell-free network massive multiple-input multiple-output

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